Fuzzy Clustering Based on Water Wave Optimization
Zifei Ren, Chunzhi Wang, Xinkai Fan, Zhiwei Ye · 2018
Fuzzy clustering is one of the most widely used and sensitive algorithms. However, one of its fatal weaknesses is that it is very sensitive to initialization and easy to get into local minima. WWO (The water wave optimization algorithm) is a widely used global optimization method. Its main advantage is simple, general and suitable for parallel processing. Thus combining optimization algorithm in waves and fuzzy clustering, can play a water wave algorithm for global optimization ability. It can give attention to both local optimization ability and improve the convergence speed at the same time, to better solve the problem of clustering. The algorithm using water wave optimization algorithm to find the optimal solution as the initial clustering center of fuzzy clustering. And then, using the fuzzy clustering to initialize clustering center. Finally obtain the global optimal solution, thus overcomes the shortcomings of fuzzy clustering.